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» Tracking Targets Via Particle Based Belief Propagation
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CVPR
2011
IEEE
13 years 1 months ago
Particle Filter with State Permutations for Solving Image Jigsaw Puzzles
We deal with an image jigsaw puzzle problem, which is defined as reconstructing an image from a set of square and non-overlapping image patches. It is known that a general instan...
Xingwei Yang, Nagesh Adluru, LonginJan Latecki
ICASSP
2007
IEEE
13 years 11 months ago
Particle PHD Filtering for Multi-Target Visual Tracking
We propose a multi-target tracking algorithm based on the Probability Hypothesis Density (PHD) filter and data association using graph matching. The PHD filter is used to compen...
Emilio Maggio, Elisa Piccardo, Carlo S. Regazzoni,...
AMDO
2010
Springer
13 years 3 months ago
Compatible Particles for Part-Based Tracking
Particle Filter methods are one of the dominant tracking paradigms due to its ability to handle non-gaussian processes, multimodality and temporal consistency. Traditionally, the e...
Brais Martínez, Marc Vivet, Xavier Binefa
IJAR
2008
119views more  IJAR 2008»
13 years 3 months ago
Least committed basic belief density induced by a multivariate Gaussian: Formulation with applications
We consider here the case where our knowledge is partial and based on a betting density function which is n-dimensional Gaussian. The explicit formulation of the least committed b...
Francois Caron, Branko Ristic, Emmanuel Duflos, Ph...
TSMC
2008
147views more  TSMC 2008»
13 years 5 months ago
Tracking of Multiple Targets Using Online Learning for Reference Model Adaptation
Recently, much work has been done in multiple ob-4 ject tracking on the one hand and on reference model adaptation5 for a single-object tracker on the other side. In this paper, we...
Franz Pernkopf